Di Fu
Impact in
- Biochemistry top 2%
- Sulfur Compounds in Biology
-
- Lymphoma Diagnosis and Treatment
Papers in
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- Insect Resistance and Genetics 4
- Cancer-related gene regulation 4
-
- Lymphoma Diagnosis and Treatment 19
- Co-authors
- Philip K. Moore (1 shared paper)Madhav Bhatia (1 shared paper)Shabbir Moochhala (1 shared paper)Pengpeng Xu (17 shared papers)Shu Cheng (16 shared papers)Li Wang (17 shared papers)Weili Zhao (16 shared papers)Hongmei Yi (11 shared papers)
- Journals
- Insects (3 papers)Signal Transduction and Targeted Therapy (3 papers)Frontiers in Oncology (3 papers)International Journal of Molecular Sciences (2 papers)Frontiers in Immunology (2 papers)
- Partner nations
- ChinaFranceUnited States
In The Last Decade
Di Fu
73 papers receiving 1.4k citations
Di Fu's Hit Papers
Peers
Comparison fields: 5 of 132
- Biochemistry 215
- Pathology and Forensic Medicine 293
- Oncology 282
- Endocrine and Autonomic Systems 68
- Cancer Research 142
Countries citing papers authored by Di Fu
This map shows the geographic impact of Di Fu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Di Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Di Fu more than expected).
Fields of papers citing papers by Di Fu
This network shows the impact of papers produced by Di Fu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Di Fu. The network helps show where Di Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Di Fu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 269 | |
| 2 | Butyrate-producing Eubacterium rectale suppresses lymphomagenesis by alleviating the TNF-induced TLR4/MyD88/NF-κB axis Hit paper breakdown → | 2022 | 135 |
| 3 | 2019 | 85 | |
| 4 | 2018 | 65 | |
| 5 | 2023 | 57 | |
| 6 | 2020 | 57 | |
| 7 | 2023 | 56 | |
| 8 | 2023 | 52 | |
| 9 | 2022 | 47 | |
| 10 | 2022 | 41 | |
| 11 | 2020 | 36 | |
| 12 | 2006 | 33 | |
| 13 | 2017 | 27 | |
| 14 | 2021 | 26 | |
| 15 | 2021 | 25 | |
| 16 | 2022 | 24 | |
| 17 | 2020 | 23 | |
| 18 | 2004 | 21 | |
| 19 | 2010 | 18 | |
| 20 | 2012 | 17 |
About Di Fu
Di Fu is a scholar working on Molecular Biology, Pathology and Forensic Medicine, Oncology, Immunology and Physiology, having authored 77 papers that have together received 1.4k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (19 papers), CAR-T cell therapy research (10 papers), Immune Cell Function and Interaction (7 papers), Pain Mechanisms and Treatments (5 papers), Insect Resistance and Genetics (4 papers), Attention Deficit Hyperactivity Disorder (4 papers), Cancer-related gene regulation (4 papers) and Rheumatoid Arthritis Research and Therapies (3 papers). The work is most often cited by research in Biochemistry (215 citations), Pathology and Forensic Medicine (293 citations), Oncology (282 citations), Endocrine and Autonomic Systems (68 citations) and Cancer Research (142 citations). Di Fu has collaborated with scholars based in China, France and United States. Frequent co-authors include Philip K. Moore, Madhav Bhatia, Shabbir Moochhala, Pengpeng Xu, Shu Cheng, Li Wang, Weili Zhao, Hongmei Yi, Weili Zhao and Yan Zhao. Their work appears in journals such as Insects, Signal Transduction and Targeted Therapy, Frontiers in Oncology, International Journal of Molecular Sciences and Frontiers in Immunology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.